The Analytic Domain of Multiple- Intelligence and Its Relation to English Objective Test
Bibliographic record
Abstract
The current research aims at identifying the analytic domain of multiple -intelligence and English objective test. The research is trying to answer that if there is a correlation between the analytic domain of multiple- intelligence and the English objective tests. Thus, the research has adopted a close questionnaire for diagnosing analytic domain (logical, rhythmic, and naturalistic) of multiple- intelligence of Iraqi students at Baghdad University, and an objective English test to achieve the aim of the research. Nine colleges at Baghdad University are randomly chosen to represent the sample of the research which is 511 students. The results of the research have shown that there are weak significant correlation between the analytic domain of multiple intelligent and the objective English test. Thus, from the results of the research Baghdad University could modify the objective tests with alternative ones that based on students’ ability and intelligence not guessing tests. Continuous long-term assessment, untimed, free- response format, individualized test and creative answers based on multiple- intelligence are recommended.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".